About

Bruce Desmarais is the DeGrandis-McCourtney Early Career Professor in Political Science at Pennsylvania State University. He serves as the Director of the Center for Social Data Analytics and is an Affiliate of the Institute for Computational and Data Sciences at Penn State. His research focuses on developing and applying social data science methods to enhance the understanding of systems of policymaking and digital communication with policymakers. Methodologically, he specializes in machine learning, network analysis, generative artificial intelligence, and causal inference. In addition to his academic roles, Desmarais is the CEO and Co-Founder of Public Square Analytics LLC, a technology and consulting firm dedicated to improving the digital public square. He earned his Ph.D. in Political Science from the University of North Carolina at Chapel Hill in 2010. Before joining Penn State, he was an Assistant Professor in the Department of Political Science and an Affiliate of the Computational Social Science Institute at UMass Amherst from 2010 to 2015.

Research topics

• Microeconomics
• Social psychology
• Market economy
• Mathematics
• Economic system
• Economic geography
• Economics
• Econometrics
• Psychology
• Macroeconomics

Selected publications

• Public Officials' Online Sharing of Low-factual Content: Institutional and Ideological Checks

  2025-05-22 · 1 citations

  preprintOpen accessSenior author

  Elected officials occupy privileged positions in public communication about important topics---roles that extend to the digital world. In the same way that public officials stand to lead constructive online dialogue, they also hold the potential to accelerate the dissemination of low-factual and harmful content. This study aims to explore and explain the sharing of low-factual content by examining nearly 500,000 Facebook posts by U.S. state legislators from 2020 to 2021. We validate a widely used low-factual content detection approach in misinformation studies, and apply the measure to all of the posts we collect. Our findings reveal that the prevalence is relatively rare, affecting less than one percent of legislators' posts overall. However, Republican legislators share low-factual content at higher rates, and certain states emerge as hotspots for such content. We also find that conservative lawmakers are more likely to share such content, with this tendency potentially intensifying in conservative districts, and waning in liberal ones. Most importantly, legislative professionalism acts as a systemic constraint: lawmakers in professionalized legislatures are less likely to share low-factual content, suggesting that high professional standards curb the spread of misinformation. We conclude with a discussion of how our results present implications for future interventions to reduce the spread of low-factual content.

  PublisherOA PDFDOI

• The digitally accountable public representation database: online communication by U.S. officials

  Scientific Data · 2025-09-25

  articleOpen accessSenior author

  We introduce the Digitally Accountable Public Representation (DAPR) Database, an innovative archive that systematically tracks and analyzes the online communication of federal, state, and local elected officials in the U.S. Focusing on X/Twitter and Facebook, the current database includes 28,834 public officials, their demographic information, and 5,769,904 X/Twitter posts along with 450,972 Facebook posts, dating from January 2020 to December 2024. The database integrates three interconnected datasets: metadata on elected officials, weekly aggregated X data, and weekly aggregated Facebook data. These weekly aggregated datasets provide detailed insights into platform activity, capturing officials' posting volumes, engagement metrics, and content trends. Our framework ensures ongoing database expansion by incorporating new officials and platforms, maintaining its relevance and research utility for analyzing officials' digital communication.

  PublisherOA PDFDOI

• Networks of inclusion: Using teams and technology to create diverse social capital

  Social Networks · 2025-06-24 · 2 citations

  articleSenior authorCorresponding
  PublisherDOI

• The Digitally Accountable Public Representation Database:Measuring Online Communication by Federal, State, and Local Officials

  2025-08-21

  articleOpen accessSenior author

  We introduce the Digitally Accountable Public Representation (DAPR) Database, an innovative archive that systematically tracks and analyzes the online communications of federal, state, and local elected officials in the U.S. Focusing on X/Twitter and Facebook, the current database includes 28,834 public officials, their demographic information, and 5,769,904 Tweets along with 450,972 Facebook posts, dating from January 2020 to December 2024. The database integrates three interconnected datasets: metadata on elected officials, weekly aggregated X data, and weekly aggregated Facebook data. These weekly aggregated datasets provide detailed insights into platform activity, capturing officials' posting volumes, engagement metrics, and content trends. Our framework ensures ongoing database expansion by incorporating new officials and platforms, maintaining its relevance and research utility for analyzing officials' digital communication.

  PublisherOA PDFDOI

• GenAI vs. Human Fact-Checkers: Accurate Ratings, Flawed Rationales

  2025-05-19 · 1 citations

  article
  PublisherDOI

• GenAI vs. Human Fact-Checkers: Accurate Ratings, Flawed Rationales

  ArXiv.org · 2025-02-20

  preprintOpen access

  Despite recent advances in understanding the capabilities and limits of generative artificial intelligence (GenAI) models, we are just beginning to understand their capacity to assess and reason about the veracity of content. We evaluate multiple GenAI models across tasks that involve the rating of, and perceived reasoning about, the credibility of information. The information in our experiments comes from content that subnational U.S. politicians post to Facebook. We find that GPT-4o, one of the most used AI models in consumer applications, outperforms other models, but all models exhibit only moderate agreement with human coders. Importantly, even when GenAI models accurately identify low-credibility content, their reasoning relies heavily on linguistic features and ``hard'' criteria, such as the level of detail, source reliability, and language formality, rather than an understanding of veracity. We also assess the effectiveness of summarized versus full content inputs, finding that summarized content holds promise for improving efficiency without sacrificing accuracy. While GenAI has the potential to support human fact-checkers in scaling misinformation detection, our results caution against relying solely on these models.

  PublisherOA PDFDOI

• Collaborative diffusion: The dynamics of policy output in <scp>COVID</scp> ‐19 interstate compacts

  Policy Studies Journal · 2025-03-29 · 1 citations

  articleOpen accessCorresponding

  Abstract Interstate compacts are formal structures through which multiple states work together towards a common goal or shared agenda. Previous research on compacts focuses almost exclusively on the decision to join the compact, leaving questions on post‐formation diffusion patterns unexplored. We use a unique case of three interstate compacts that form simultaneously around the same issue—the COVID‐19 pandemic—to test how policy diffuses within compacts. We employ a novel diffusion methodology, network event history analysis (NEHA), to determine the role of compact membership in policy activity. We find that compact member states are no more active in adopting policy than non‐members, but that non‐member states use compacts to free ride when making their own adoption choices. We find that compacts serve to establish members as leaders, as non‐members' policy adoptions are strongly driven by the adoptions of compact members. We also find COVID‐19 policy diffusion to be strongly driven by state ideology.

  PublisherOA PDFDOI

• Political Elites in the Attention Economy: Visibility Over Civility and Credibility?

  Proceedings of the International AAAI Conference on Web and Social Media · 2025-06-07 · 4 citations

  articleOpen accessSenior author

  Elected officials have privileged roles in public communication. In contrast to national politicians, whose posting content is more likely to be closely scrutinized by a robust ecosystem of nationally focused media outlets, sub-national politicians are more likely to openly disseminate harmful content with limited media scrutiny. In this paper, we analyze the factors that explain the online visibility of over 6.5K unique state legislators in the US and how their visibility might be impacted by posting low-credibility or uncivil content. We conducted a study of posting on Twitter and Facebook (FB) during 2020-21 to analyze how legislators engage with users on these platforms. The results indicate that distributing content with low-credibility information attracts greater attention from users on FB and Twitter for Republicans. Conversely, posting content that is considered uncivil on Twitter receives less attention. A noticeable scarcity of posts containing uncivil content was observed on FB, which may be attributed to the different communication patterns of legislators on these platforms. In most cases, the effect is more pronounced among the most ideologically extreme legislators. Our research explores the influence exerted by state legislators on online political conversations, with Twitter and FB serving as case studies. Furthermore, it sheds light on the differences in the conduct of political actors on these platforms. This study contributes to a better understanding of the role that political figures play in shaping online political discourse.

  PublisherOA PDFDOI

• The Digitally Accountable Public Representation Database:Measuring Online Communication by Federal, State, and Local Officials

  2025-03-24

  preprintOpen accessSenior author

  We introduce the Digitally Accountable Public Representation (DAPR) Database, an innovative archive that systematically tracks and analyzes the online communications of federal, state, and local elected officials in the U.S. Focusing on X/Twitter and Facebook, the current database includes 28,980 public officials, their demographic information, and 5,769,904 Tweets along with 450,972 Facebook posts, dating from January 2020 to December 2024. The database integrates three interconnected datasets: metadata on elected officials, and weekly aggregated platform data for Facebook and X. These weekly aggregated datasets provide detailed insights into platform activity, capturing officials' posting volumes, engagement metrics, and content trends. Our framework ensures ongoing database expansion by incorporating new officials and platforms, maintaining its relevance and research utility for analyzing officials' digital communication.

  PublisherOA PDFDOI

• Political Elites in the Attention Economy: Visibility Over Civility and Credibility?

  arXiv (Cornell University) · 2024-07-22 · 2 citations

  preprintOpen accessSenior author

  Elected officials have privileged roles in public communication. In contrast to national politicians, whose posting content is more likely to be closely scrutinized by a robust ecosystem of nationally focused media outlets, sub-national politicians are more likely to openly disseminate harmful content with limited media scrutiny. In this paper, we analyze the factors that explain the online visibility of over 6.5K unique state legislators in the US and how their visibility might be impacted by posting low-credibility or uncivil content. We conducted a study of posting on Twitter and Facebook (FB) during 2020-21 to analyze how legislators engage with users on these platforms. The results indicate that distributing content with low-credibility information attracts greater attention from users on FB and Twitter for Republicans. Conversely, posting content that is considered uncivil on Twitter receives less attention. A noticeable scarcity of posts containing uncivil content was observed on FB, which may be attributed to the different communication patterns of legislators on these platforms. In most cases, the effect is more pronounced among the most ideologically extreme legislators. Our research explores the influence exerted by state legislators on online political conversations, with Twitter and FB serving as case studies. Furthermore, it sheds light on the differences in the conduct of political actors on these platforms. This study contributes to a better understanding of the role that political figures play in shaping online political discourse.

  PublisherOA PDFDOI

Recent grants

• Collaborative Research: HNDS-I: Digitally Accountable Public Representation

  NSF · $649k · 2023–2026

• Collaborative Research: An Expanded Framework for Inferring Public Policy Diffusion Networks

  NSF · $179k · 2016–2020

• RAPID: Collaborative Research: The Diffusion of State Policy Responses to the 2019 Novel Coronavirus

  NSF · $16k · 2020–2022

• Collaborative Research: Specification and Estimation of Exponential Family Random Graph Models for Weighted Networks

  NSF · $78k · 2014–2016

• Collaborative Research: Patterns, Context, and Secondary Impacts of State Policy Responses to the Pandemic

  NSF · $366k · 2022–2025

Frequent coauthors

• Skyler Cranmer

  49 shared

• Jeffrey J. Harden

  University of Notre Dame

  39 shared

• Frederick J. Boehmke

  University of Iowa

  34 shared

• John Hird

  28 shared

• Hanna Wallach

  26 shared

• Steven Smith

  18 shared

• Fridolin Linder

  Pennsylvania State University

  15 shared

• Nadia E. Brown

  Pinsent Masons (United Kingdom)

  14 shared

Education

• PhD, Political Science

  University of North Carolina at Chapel Hill

  2010

• BA, Economics and Political Science

  Eastern Connecticut State University

  2005